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The "AWS Architect Full Course" is a thorough learning experience designed to help aspiring AWS architects gain essential knowledge. This Full Course covers core AWS services, best practices, security, and advanced topics such as serverless computing, giving you practical insights into designing and managing scalable solutions on the AWS cloud.

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Dr. Paul Lessard and his collaborators have written a paper on "Categorical Deep Learning and Algebraic Theory of Architectures". They aim to make neural networks more interpretable, composable and amenable to formal reasoning. The key is mathematical abstraction, as exemplified by category theory - using monads to develop a more principled, algebraic approach to structuring neural networks.

We also discussed the limitations of current neural network architectures in terms of their ability to generalise and reason in a human-like way. In particular, the inability of neural networks to do unbounded computation equivalent to a Turing machine. Paul expressed optimism that this is not a fundamental limitation, but an artefact of current architectures and training procedures.

The power of abstraction - allowing us to focus on the essential structure while ignoring extraneous details. This can make certain problems more tractable to reason about. Paul sees category theory as providing a powerful "Lego set" for productively thinking about many practical problems.

Towards the end, Paul gave an accessible introduction to some core concepts in category theory like categories, morphisms, functors, monads etc. We explained how these abstract constructs can capture essential patterns that arise across different domains of mathematics.

Paul is optimistic about the potential of category theory and related mathematical abstractions to put AI and neural networks on a more robust conceptual foundation to enable interpretability and reasoning. However, significant theoretical and engineering challenges remain in realising this vision.

Please support us on Patreon. We are entirely funded from Patreon donations right now.
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If you would like to sponsor us, so we can tell your story - reach out on mlstreettalk at gmail

Links:
Categorical Deep Learning: An Algebraic Theory of Architectures
Bruno Gavranović, Paul Lessard, Andrew Dudzik,
Tamara von Glehn, João G. M. Araújo, Petar Veličković
Paper: https://categoricaldeeplearning.com/

Symbolica:
https://twitter.com/symbolica
https://www.symbolica.ai/

Dr. Paul Lessard (Principal Scientist - Symbolica)
https://www.linkedin.com/in/paul-roy-lessard/

Neural Networks and the Chomsky Hierarchy (Grégoire Delétang et al)
https://arxiv.org/abs/2207.02098

Interviewer: Dr. Tim Scarfe

Pod: https://podcasters.spotify.com..../pod/show/machinelea

Transcript:
https://docs.google.com/docume....nt/d/1NiHJKTkeqYdpcg

More info about NNs not being recursive/TMs:
https://www.youtube.com/watch?v=4KIQH1VEwBI

Geometric Deep Learning blueprint:
https://www.youtube.com/watch?v=bIZB1hIJ4u8

TOC:
00:00:00 - Intro
00:05:07 - What is the category paper all about
00:07:19 - Composition
00:10:42 - Abstract Algebra
00:23:01 - DSLs for machine learning
00:24:10 - Inscrutability
00:29:04 - Limitations with current NNs
00:30:41 - Generative code / NNs don't recurse
00:34:34 - NNs are not Turing machines (special edition)
00:53:09 - Abstraction
00:55:11 - Category theory objects
00:58:06 - Cat theory vs number theory
00:59:43 - Data and Code are one and the same
01:08:05 - Syntax and semantics
01:14:32 - Category DL elevator pitch
01:17:05 - Abstraction again
01:20:25 - Lego set for the universe
01:23:04 - Reasoning
01:28:05 - Category theory 101
01:37:42 - Monads
01:45:59 - Where to learn more cat theory

Learn Calculus 1 in this full college course.

This course was created by Dr. Linda Green, a lecturer at the University of North Carolina at Chapel Hill. Check out her YouTube channel: https://www.youtube.com/channe....l/UCkyLJh6hQS1TlhUZx

This course combines two courses taught by Dr. Green. She teaches both Calculus 1 and a Calculus 1 Corequisite course, designed to be taken at the same time. In this video, the lectures from the Corquisite course, which review important Algebra and Trigonometry concepts, have been interspersed with the Calculus 1 lectures at the places suggested by Dr. Green.

⭐️ Prerequisites ⭐️
🎥 Algebra: https://www.youtube.com/watch?v=LwCRRUa8yTU
🎥 Precalculus: https://www.youtube.com/watch?v=eI4an8aSsgw

⭐️ Lecture Notes ⭐️
🔗 Calculus 1 Corequisite Notes: http://lindagreen.web.unc.edu/....files/2020/08/course
🔗 Calculus 1 Notes: http://lindagreen.web.unc.edu/....files/2019/12/course

⭐️ Course Contents ⭐️
(0:00:00) [Corequisite] Rational Expressions
(0:09:40) [Corequisite] Difference Quotient
(0:18:20) Graphs and Limits
(0:25:51) When Limits Fail to Exist
(0:31:28) Limit Laws
(0:37:07) The Squeeze Theorem
(0:42:55) Limits using Algebraic Tricks
(0:56:04) When the Limit of the Denominator is 0
(1:08:40) [Corequisite] Lines: Graphs and Equations
(1:17:09) [Corequisite] Rational Functions and Graphs
(1:30:35) Limits at Infinity and Graphs
(1:37:31) Limits at Infinity and Algebraic Tricks
(1:45:34) Continuity at a Point
(1:53:21) Continuity on Intervals
(1:59:43) Intermediate Value Theorem
(2:03:37) [Corequisite] Right Angle Trigonometry
(2:11:13) [Corequisite] Sine and Cosine of Special Angles
(2:19:16) [Corequisite] Unit Circle Definition of Sine and Cosine
(2:24:46) [Corequisite] Properties of Trig Functions
(2:35:25) [Corequisite] Graphs of Sine and Cosine
(2:41:57) [Corequisite] Graphs of Sinusoidal Functions
(2:52:10) [Corequisite] Graphs of Tan, Sec, Cot, Csc
(3:01:03) [Corequisite] Solving Basic Trig Equations
(3:08:14) Derivatives and Tangent Lines
(3:22:55) Computing Derivatives from the Definition
(3:34:02) Interpreting Derivatives
(3:42:33) Derivatives as Functions and Graphs of Derivatives
(3:56:25) Proof that Differentiable Functions are Continuous
(4:01:09) Power Rule and Other Rules for Derivatives
(4:07:42) [Corequisite] Trig Identities
(4:15:14) [Corequisite] Pythagorean Identities
(4:20:35) [Corequisite] Angle Sum and Difference Formulas
(4:28:31) [Corequisite] Double Angle Formulas
(4:36:01) Higher Order Derivatives and Notation
(4:39:22) Derivative of e^x
(4:46:52) Proof of the Power Rule and Other Derivative Rules
(4:56:31) Product Rule and Quotient Rule
(5:02:09) Proof of Product Rule and Quotient Rule
(5:10:40) Special Trigonometric Limits
(5:17:31) [Corequisite] Composition of Functions
(5:29:54) [Corequisite] Solving Rational Equations
(5:40:02) Derivatives of Trig Functions
(5:46:23) Proof of Trigonometric Limits and Derivatives
(5:54:38) Rectilinear Motion
(6:11:41) Marginal Cost
(6:16:51) [Corequisite] Logarithms: Introduction
(6:25:32) [Corequisite] Log Functions and Their Graphs
(6:36:17) [Corequisite] Combining Logs and Exponents
(6:40:55) [Corequisite] Log Rules
(6:49:27) The Chain Rule
(6:58:44) More Chain Rule Examples and Justification
(7:07:43) Justification of the Chain Rule
(7:10:00) Implicit Differentiation
(7:20:28) Derivatives of Exponential Functions
(7:25:38) Derivatives of Log Functions
(7:29:38) Logarithmic Differentiation
(7:37:08) [Corequisite] Inverse Functions
(7:51:22) Inverse Trig Functions
(8:00:56) Derivatives of Inverse Trigonometric Functions
(8:12:11) Related Rates - Distances
(8:17:55) Related Rates - Volume and Flow
(8:22:21) Related Rates - Angle and Rotation
(8:28:20) [Corequisite] Solving Right Triangles
(8:34:54) Maximums and Minimums
(8:46:18) First Derivative Test and Second Derivative Test
(8:51:37) Extreme Value Examples
(9:01:33) Mean Value Theorem
(9:09:09) Proof of Mean Value Theorem
(0:14:59) [Corequisite] Solving Right Triangles
(9:25:20) Derivatives and the Shape of the Graph
(9:33:31) Linear Approximation
(9:48:28) The Differential
(9:59:11) L'Hospital's Rule
(10:06:27) L'Hospital's Rule on Other Indeterminate Forms
(10:16:13) Newtons Method
(10:27:45) Antiderivatives
(10:33:24) Finding Antiderivatives Using Initial Conditions
(10:41:59) Any Two Antiderivatives Differ by a Constant
(10:45:19) Summation Notation
(10:49:12) Approximating Area
(11:04:22) The Fundamental Theorem of Calculus, Part 1
(11:15:02) The Fundamental Theorem of Calculus, Part 2
(11:22:17) Proof of the Fundamental Theorem of Calculus
(11:29:18) The Substitution Method
(11:38:07) Why U-Substitution Works
(11:40:23) Average Value of a Function
(11:47:57) Proof of the Mean Value Theorem for Integrals

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This Machine Learning tutorial video is ideal for beginners to learn Machine Learning from scratch. By the end of this tutorial video, you will learn why Machine Learning is so important in our lives, what is Machine Learning, the various types of Machine Learning (Supervised, Unsupervised and Reinforcement learning), .

This Machine Learning tutorial will cover the following topics:
1. Life without Machine Learning ( 01:06 )
2. Life with Machine Learning ( 02:29 )
3. What is Machine Learning ( 04:35 )
4. Machine Learning Process ( 05:27 )
5. Types of Machine Learning ( 06:14 )
6. Supervised Vs Unsupervised ( 09:32 )
7. The right Machine Learning solutions ( 10:35 )
8. Machine Learning Algorithms ( 13:33 )
9. Use case - Predicting the price of a house using Linear Regression ( 23:24 )

What is Machine Learning: Machine Learning is an application of Artificial Intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed.

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This video on complete excel course - beginner to expert by Simplilearn is complete Excel tutorial that helps aspiring data analysts with excel data analytics fundamentals.

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Excel Basic Knowledge
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In this video on What is Search Engine Marketing, embark on a journey into the realm of Search Engine Marketing (SEM). Explore the fundamental concepts, unraveling the importance of SEM in today's digital landscape. We'll dive into the SEM vs. SEO comparison, understanding the nuances between these crucial strategies. Discover the inner workings of SEM, from the selection of keywords to the dynamics of ad auctions. Learn about essential SEM tools that empower successful campaigns. Gain insights into the intriguing world of ad auctions and explore effective SEM campaign strategies to enhance online visibility.

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✅ About Post Graduate Program in Digital Marketing Program:
This digital marketing course is meant for professionals looking to pursue a Digital Marketing career, know the fundamentals, and gain hands-on experience, as well as experienced marketers keen on learning the latest Digital Marketing skills. The Harvard Business case studies and projects on Google and Facebook add real-world experience.

✅ Key Features:
- Purdue-Simplilearn Joint Post Graduate Program Certification
- Purdue Alumni Membership and Masterclasses
- Masterclasses from top Purdue instructors
- 200+ hours of applied learning
- Experiential learning through case studies and theme-based project work
- Get noticed by the top hiring companies
- Learn 35+ Digital Marketing tools

✅ Skills Covered

- Search Engine Optimization
- Content Marketing
- Web Analytics
- Keyword Management and Research
- Website Management and Optimization
- URL Management
- Search Psychology
- Keyword Organization and Match Types
- Keyword Research
- Advanced Ad Features
- Ad Testing and ExtensionsLanguage Targeting
- And Many More
Note: 1 year of experience is preferred

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#MachineLearningInterviewQuestions #MLInterviewQuestions #MLInterviewPreparation #MachineLearningEngineerInterviewQuestions #MachineLearningInterview #MachineLearningInterviewQuestionsForFreshers #Intellipaat

This video, Top 30 Machine Learning Interview Questions 2025, brings you the most frequently asked questions and detailed answers to ace your next job interview. Whether you're a fresher or an experienced professional, these machine learning interview questions are designed to help you prepare effectively for roles like Machine Learning Engineer, Data Scientist, or AI Specialist.

Discover insights into key ML concepts, algorithms, and problem-solving techniques that hiring managers value. Learn about important machine learning interview questions and their answers. With this ML interview questions and answers for experienced and freshers guide, become confident in answering questions about various machine learning concepts. Look into the critical questions around concepts such as supervised and unsupervised learning, feature selection, model evaluation, and advanced ML techniques. Don't miss this video, because this is going to enhance your understanding of machine learning and going to help you crack your dream job. Watch now and get ready to shine in your ML interviews!

📖Below are the pointers covered in this 'ML Interview Questions and Answers' video:

🥇 00:00:00 - Introduction to Machine Learning Interview Questions

👨‍💻 ML Interview Questions for Freshers (Basic Level Machine Learning Engineer Interview Questions):
Q1. What is Machine Learning, and why is it important?
Q2. Differentiate between supervised, unsupervised, and reinforcement learning.
Q3. What is a model in machine learning, and how is it used?
Q4. Explain overfitting and underfitting with examples.
Q5. What is a confusion matrix, and how is it used in evaluating models?
Q6. Define cross-validation. Why is it important in model evaluation?
Q7. What is the role of precision and recall in evaluating a model?
Q8. What is the F1 score, and how is it calculated?
Q9. What is the purpose of regularization in machine learning?
Q10. Explain the bias-variance trade-off.

👨‍💻 Intermediate Level Machine Learning Interview Questions:
Q11. What is feature engineering, and why is it crucial in machine learning?
Q12. Example of when a False positive is more crucial than a false negative and vice versa
Q13. What does naivety stand for in naive Bayes?
Q14. Give an example where the median is a better measure than the mean.
Q15. What are the key differences between bagging and boosting in ensemble methods?
Q16. How does a decision tree work in machine learning?
Q17. What is the principal component analysis (PCA), and when should it be used?
Q18. How does a support vector machine (SVM) classify data?
Q19. What is a dropout in neural networks, and how does it prevent overfitting?
Q20. Differentiate between batch gradient descent and stochastic gradient descent.

👨‍💻 Advanced Level Machine Learning Interview Questions for Experienced:
Q21. You notice that your model is overfitting on the training data. What steps would you take to address this issue?
Q22. How would you evaluate a model's performance using a Receiver Operating Characteristic (ROC) curve?
Q23. Describe a situation where regularization (L1 or L2) significantly improved your model's performance.
Q24. You are given a dataset with imbalanced classes. How would you handle this during model training?
Q25. Explain GAN.
Q26. Explain CNN.
Q27. Explain how recurrent neural networks (RNNs) are used for time-series data. Provide an example.
Q28. What strategy would you use to tune hyperparameters for a Random Forest or gradient-boosting model?
Q29. Describe a real-world scenario where reinforcement learning could be applied effectively.
Q30. How would you optimize the training of a deep neural network on a large-scale dataset with limited computational resources?

✅ How do I prepare for a machine learning interview?
Preparing for a machine learning interview involves mastering the fundamentals of ML concepts like supervised and unsupervised learning, algorithms, and model evaluation techniques. Work on real-world ML projects to showcase hands-on experience and build a strong portfolio.

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This Gen AI Full Course video by simplilearn helps us learn everything about Generative AI. The Introduction to Gen AI Full Course covers key topics such as What is AI and How it Works, the Evolution of AI, and a Roadmap to Become a Gen AI Engineer, along with advanced subjects like Generative Adversarial Tutorial, Transformers in AI, Langchain, ML Projects for Resume, and Top 10 AI Technologies, including deep dives into OpenAI ChatGPT-01 Model, LLM Benchmarking, and AI Career Opportunities.

Following are the topics covered in the Gen AI Full Course:

00:00:00 Introduction to Gen AI Full Course
00:08:08 Introduction to What is AI and How it works
00:08:53 What is Gen AI
00:19:32 Roadmap to become a Gen AI Engineer
00:35:11 AI Trends for future
00:36:31 Evolution of AI
01:00:50 Open ai chatgpt o1 model
01:02:40 AI Carrer opportunities
01:10:03 Top 10 AI Technologies
01:25:03 Deep Learning
01:33:20 Search GPT
01:35:35 Langchain
01:48:06 ML Projects for resume
02:50:29 Generative Adversarial Tutorial
02:59:51 What are Gans
03:00:52 Transformers in AI
03:13:21 LSTM
03:14:36 Gen Ai vs AI
03:23:39 Introduction to LLM
04:24:52 What is ML
05:21:24 ML Tutorial for beginners
07:26:47 Reinforcement Learning
08:56:26 Recurrent Neural Network
09:16:17 CHatgpt analyse
09:25:10 LLM Benchmarkeing
10:15:53 Hugging Face and its tutorial

✅ What is Gen AI?
Generative artificial intelligence, also known as generative AI or gen AI for short, is a type of artificial intelligence (AI) that can create new content and ideas, including conversations, stories, images, videos, and music. It can learn human language, programming languages, art, chemistry, biology, or any complex subject matter. It reuses what it knows to solve new problems.

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➡️ About Professional Certificate Program in Generative AI and Machine Learning

The Generative AI and Machine Learning course enriches your career journey with comprehensive coverage of machine learning, deep learning, NLP, generative AI, reinforcement learning, computer vision, and more. Combining theory with hands-on practice, it offers live virtual sessions, projects with integrated labs, and masterclasses by IIT Guwahati faculty.

Key Features

✅ Program completion certificate from E&ICT Academy, IIT Guwahati
✅ Curriculum delivered in live virtual classes by seasoned industry experts
✅ Exposure to the latest AI advancements, such as generative AI, LLMs, and prompt engineering
✅ Interactive live-virtual masterclasses delivered by esteemed IIT Guwahati faculty
✅ Opportunity to earn an Executive Alumni Status from E&ICT Academy, IIT Guwahati
✅ Eligibility for a campus immersion program organized at IIT Guwahati
✅ Exclusive hackathons and “ask-me-anything” sessions by IBM
✅ Certificates for IBM courses and industry masterclasses by IBM experts
✅ Practical learning through 25+ hands-on projects and 3 industry-oriented capstone projects
✅ Access to a wide array of AI tools such as ChatGPT, Hugging Face, DALL-E 2, Midjourney and more
✅ Simplilearns JobAssist helps you get noticed by top hiring companies

Learning Path
✅ IITG AI: Program Induction
✅ IITG AI: Programming Fundamentals
✅ IITG AI: Python for Data Science (IBM)
✅ IITG AI: Applied Data Science with Python
✅ IITG AI: Machine Learning
✅ IITG AI: Deep Learning with TensorFlow (IBM)
✅ IITG AI: Deep Learning Specialization
✅ IITG AI: Essentials of Generative AI, Prompt Engineering & ChatGPT
✅ IITG AI: Advanced Generative AI

Skills Covered

✅ Generative AI
✅ Prompt Engineering
✅ Chatbot Development
✅ Supervised and Unsupervised Learning
✅ Model Training and Optimization
✅ Model Evaluation and Validation
✅ Ensemble Methods
✅ Deep Learning
✅ Natural Language Processing
✅ Computer Vision
✅ Reinforcement Learning
✅ Machine Learning Algorithms
✅ Speech Recognition
✅ Statistics

👉 Enroll Now: https://www.simplilearn.com/iitg-generative-ai-machine-learning-program?utm_campaign=W7Yrx_IdIiY&utm_medium=Description&utm_source=Youtube

*Note: 1+ Years of Work Experience Recommended to Sign up for Below Programs⬇️
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🔥Big Data Engineer Masters Program (Discount Code - YTBE15): https://www.simplilearn.com/big-data-engineer-masters-program?utm_campaign=BigData-aReuLtY0YMI-aReuLtY0YMI&utm_medium=Descriptionff&utm_source=youtube
Hadoop is a famous Big Data framework; this video on Hadoop will acquaint you with the term Big Data and help you understand the importance of Hadoop. Here, you will also learn about the three main components of Hadoop, namely, HDFS, MapReduce, and YARN. In the end, we will have a quiz on Hadoop. Hadoop is a framework that manages Big Data storage in a distributed way and processes it parallelly. Now, let's get started and learn all about Hadoop.

Don't forget to take the quiz at 05:11!

To learn more about Hadoop, subscribe to our YouTube channel: https://www.youtube.com/user/S....implilearn?sub_confi

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➡️ Post Graduate Program In Data Engineering
This Data Engineering course is ideal for professionals, covering critical topics like the Hadoop framework, Data Processing using Spark, Data Pipelines with Kafka, Big Data on AWS, and Azure cloud infrastructures. This program is delivered via live sessions, industry projects, masterclasses, IBM hackathons, and Ask Me Anything sessions.

✅ Key Features
- Professional Certificate Program Certificate and Alumni Association membership
- Exclusive Master Classes and Ask me Anything sessions by IBM
- 8X higher live interaction in live Data Engineering online classes by industry experts
- Capstone from 3 domains and 14+ Projects with Industry datasets from YouTube, Glassdoor, Facebook etc.
- Master Classes delivered by Purdue faculty and IBM experts
- Simplilearn's JobAssist helps you get noticed by top hiring companies

✅ Skills Covered
- Real Time Data Processing
- Data Pipelining
- Big Data Analytics
- Data Visualization
- Provisioning data storage services
- Apache Hadoop
- Ingesting Streaming and Batch Data
- Transforming Data
- Implementing Security Requirements
- Data Protection
- Encryption Techniques
- Data Governance and Compliance Controls

👉Learn More at: https://www.simplilearn.com/pgp-data-engineering-certification-training-course?utm_campaign=BigData-aReuLtY0YMI&utm_medium=Description&utm_source=youtube

🔥🔥 Interested in Attending Live Classes? Call Us: IN - 18002127688 / US - +18445327688

🎓Enhance your expertise in the below technologies to secure lucrative, high-paying job opportunities:
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🔥 Edureka R Training (Use Code "𝐘𝐎𝐔𝐓𝐔𝐁𝐄𝟐𝟎") : https://www.edureka.co/data-an....alytics-with-r-certi
This Edureka R Tutorial (R Tutorial Blog: https://goo.gl/mia382) will help you in understanding the fundamentals of R tool and help you build a strong foundation in R. Below are the topics covered in this tutorial:

1. Why do we need Analytics ?
2. What is Business Analytics ?
3. Why R ?
4. Variables in R
5. Data Operator
6. Data Types
7. Flow Control
8. Plotting a graph in R

Check out our R Playlist: https://goo.gl/huUh7Y

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How it Works?

1. This is a 5 Week Instructor led Online Course, 30 hours of assignment and 20 hours of project work

2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course.

3. At the end of the training you will be working on a real time project for which we will provide you a Grade and a Verifiable Certificate!
- - - - - - - - - - - - - - - - -

About the Course
edureka's Data Analytics with R training course is specially designed to provide the requisite knowledge and skills to become a successful analytics professional. It covers concepts of Data Manipulation, Exploratory Data Analysis, etc before moving over to advanced topics like the Ensemble of Decision trees, Collaborative filtering, etc. During our Data Analytics with R Certification training, our instructors will help you:

1. Understand concepts around Business Intelligence and Business Analytics

2. Explore Recommendation Systems with functions like Association Rule Mining , user-based collaborative filtering and Item-based collaborative filtering among others

3. Apply various supervised machine learning techniques

4. Perform Analysis of Variance (ANOVA)

5. Learn where to use algorithms - Decision Trees, Logistic Regression, Support Vector Machines, Ensemble Techniques etc

6. Use various packages in R to create fancy plots

7. Work on a real-life project, implementing supervised and unsupervised machine learning techniques to derive business insights


- - - - - - - - - - - - - - - - - - -

Who should go for this course?

This course is meant for all those students and professionals who are interested in working in analytics industry and are keen to enhance their technical skills with exposure to cutting-edge practices. This is a great course for all those who are ambitious to become 'Data Analysts' in near future. This is a must learn course for professionals from Mathematics, Statistics or Economics background and interested in learning Business Analytics.

- - - - - - - - - - - - - - - -

Why learn Data Analytics with R?

The Data Analytics with R training certifies you in mastering the most popular Analytics tool. "R" wins on Statistical Capability, Graphical capability, Cost, rich set of packages and is the most preferred tool for Data Scientists.

Below is a blog that will help you understand the significance of R and Data Science: Mastering R Is The First Step For A Top-Class Data Science Career

Having Data Science skills is a highly preferred learning path after the Data Analytics with R training. Check out the upgraded Data Science Course

For more information, please write back to us at sales@edureka.co or call us at IND: 9606058406 / US: 18338555775 (toll-free).

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In this video, Top 10 No-Code App Builders in 2025, we explore the best platforms that let you create apps without writing any code. No-code tools have become more powerful, allowing anyone—from beginners to businesses—to build mobile and web apps easily. We’ll start by explaining how no-code platforms work, from setting up a database to designing your app and automating workflows. Then, we’ll dive into the top 10 no-code app builders, including Softr, Bubble, Glide, Adalo, and more. Some platforms are great for beginners, while others offer advanced features to build full-scale applications. Whether you want to launch a simple project, create a business tool, or build a scalable app, this video will help you find the best platform. No-code is changing the way apps are built, making development faster and more accessible.

00:00:00 – Introduction
00:01:15 – Step 1: Creating a Database
00:01:30 – Step 2: Building the User Interface
00:01:45 – Step 3: Logic and Automation
00:01:48 – 1. Softr
00:07:14 – 2. Bubble
00:11:15 – 3. Glide
00:14:52 – 4. Adalo
00:16:52 – 5. Backendless
00:18:54 – 6. Quickbase
00:20:06 – 7. Zapier Interfaces
00:22:17 – 8. FlutterFlow + Firebase
00:24:34 – 9. WeWeb + Xano
00:26:20 – 10. Bravo Studio

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➡️ About Professional Certificate Program in Generative AI and Machine Learning

Dive into the future of AI with our Generative AI & Machine Learning course, in collaboration with E&ICT Academy, IIT Guwahati. Learn tools like ChatGPT, OpenAI, Hugging Face, Python, and more. Join masterclasses led by IITG faculty, engage in hands-on projects, and earn Executive Alumni Status.

Key Features:
✅ Program completion certificate from E&ICT Academy, IIT Guwahati
✅ Curriculum delivered in live virtual classes by seasoned industry experts
✅ Exposure to the latest AI advancements, such as generative AI, LLMs, and prompt engineering
✅ Interactive live-virtual masterclasses delivered by esteemed IIT Guwahati faculty
✅ Opportunity to earn an 'Executive Alumni Status' from E&ICT Academy, IIT Guwahati
✅ Eligibility for a campus immersion program organized at IIT Guwahati
✅ Exclusive hackathons and “ask-me-anything” sessions by IBM
✅ Certificates for IBM courses and industry masterclasses by IBM experts
✅ Practical learning through 25+ hands-on projects and 3 industry-oriented capstone projects
✅ Access to a wide array of AI tools such as ChatGPT, Hugging Face, DALL-E 2, Midjourney and more
✅ Simplilearn's JobAssist helps you get noticed by top hiring companies

Skills Covered:
✅ Generative AI
✅ Prompt Engineering
✅ Chatbot Development
✅ Supervised and Unsupervised Learning
✅ Model Training and Optimization
✅ Model Evaluation and Validation
✅ Ensemble Methods
✅ Deep Learning
✅ Natural Language Processing
✅ Computer Vision
✅ Reinforcement Learning
✅ Machine Learning Algorithms
✅ Speech Recognition
✅ Statistics

Learning Path:
✅ IITG AI: Program Induction
✅ IITG AI: Programming Fundamentals
✅ IITG AI: Python for Data Science (IBM)
✅ IITG AI: Applied Data Science with Python
✅ IITG AI: Machine Learning
✅ IITG AI: Deep Learning with TensorFlow (IBM)
✅ IITG AI: Deep Learning Specialization
✅ IITG AI: Essentials of Generative AI, Prompt Engineering & ChatGPT
✅ IITG AI: Advanced Generative AI
✅ IITG AI: Capstone
Electives:
✅ IITG AI: ADL & Computer Vision
✅ IITG AI: NLP and Speech Recognition
✅ IITG AI: Reinforcement Learning
✅ IITG AI: Academic Masterclass
✅ IITG AI: Industry Masterclass

👉 Learn More At: https://www.simplilearn.com/iitg-generative-ai-machine-learning-program?utm_campaign=cCYYv93MSCQ&utm_medium=Description&utm_source=Youtube

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The Penetration Testing Full Course by Simplilearn covers essential topics in cybersecurity and ethical hacking. It starts with a cybersecurity tutorial for beginners, followed by an overview of ethical hacking and penetration testing basics. The course explores cybersecurity career roadmaps, salaries for penetration testers, and top cybersecurity certifications. Learners can discover hacking gadgets, phishing attacks, and Wireshark tutorials for network analysis. The course also introduces EthicalHacker GPT and highlights common cybersecurity mistakes and interview questions for aspiring professionals.

The following are the topics covered in the Penetration Testing Full Course:

00:00:00 Introduction to Penetration Testing Full Course
00:14:24 Cyber Security Tutorial For Beginners
00:22:19 What is Ethical Hacking
00:36:13 Top 5 Cybersecurity Certifications
01:01:34 Penetration Testing Tutorial for beginners
01:14:06 Cybersecurity Engineer roadmap
01:21:24 Penetration Tester Salary
03:56:50 Ethical Hacking Tutorial For Beginners
03:57:33 Top 7 Dangerous Hacking Gadgets
04:16:01 Phishing Attacks
04:33:30 EthicalHacker GPT
Toughest Cybersecurity Certifications
Common Cybersecurity Mistakes
Wireshark tutorial for beginners
Cyber security Interview Questions

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⏩ Check out the Cyber Security training videos: https://www.youtube.com/playli....st?list=PLEiEAq2VkUU

#ethicalhacking #cybersecurity #cybersecuritycertification #cybersecuritytutorial #simplilearn #2025

What Is Penetration Testing in Cyber Security?
Penetration testing is a controlled form of hacking into a web application or a mobile application, cyber security experts use ethical hacking techniques to find the flaws and then try to fix weaknesses. The results of a penetration test can be used to improve a system's security posture and patch vulnerabilities.

➡️ About Cyber Security Expert Masters Program
This cybersecurity expert program readies individuals for CEH, CompTIA Security+, and CISSP certifications, offering a holistic defense strategy against dynamic cyber threats. CEH emphasizes ethical hacking, CompTIA focuses on foundational security concepts, and CISSP covers advanced principles and management.

✅ Key Features
- Simplilearn's JobAssist helps you get noticed by top hiring companies
- Get Lifetime access to self-paced videos
- CEH Exam Voucher with 6 months of complimentary iLabs access
- Live Classes by Accredited instructors
- Earn the requisite 30 CPEs required to take up the CISSP certification exam.
- Simulation tests focused on exam preparation

✅ Skills Covered
- Network Security
- Risk Management
- Network Packet Analysis
- Asset Security
- Disaster Recovery
- Encryption
- System Hacking
- Malware Threats
- Planning and Monitoring
- Identity and Access Management
- Forensics
- Cryptography
- System Penetration Testing
- Incident Management
- Pen Testing
- Vulnerability Analysis
- Software Development Security

🔥🔥 Interested in Attending Live Classes? Call Us: IN - 18002127688 / US - +18445327688

🔥𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐌𝐢𝐜𝐫𝐨𝐬𝐨𝐟𝐭 𝐀𝐳𝐮𝐫𝐞 𝐃𝐞𝐯𝐎𝐩𝐬 𝐒𝐨𝐥𝐮𝐭𝐢𝐨𝐧𝐬 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧: https://www.edureka.co/microso....ft-azure-devops-solu
This Edureka live video on Azure DevOps Full Course will give you a detailed study introduction on how you can implement DevOps practices on Microsoft Azure. Topics Covered :
00:00:00 Introduction
00:01:25 Agenda
00:02:51 What is Azure?
00:06:40 What is Cloud Computing
00:14:07 Microsoft Azure
00:14:14 How to launch these services in Azure
00:29:51 Demo
00:47:59 Azure Certification
00:49:40 Types of Azure Certifications
00:58:55 How to create azure Free Account
01:04:26 Azure Portals
01:18:29 Azure Virtual Machine
01:22:36 Azure VM Architecture
01:31:33 Azure VM Hands-on
01:39:54 Introduction to Azure Kubernetes Services
01:46:12 Container Vs VM
01:51:14 What is Kubernetes
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02:29:31 ARM Templates
02:52:31 Demo
02:57:48 What is Azure Active Directory
03:02:35 Service Audience
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03:06:29 Demo
03:24:31 Introduction to DevOps
03:47:45 DevOps Tools
04:09:24 DevOps Automation
04:12:17 What is Git?
04:36:47 Git Operations & Commands
05:04:39 Introduction to SSH Keys
05:06:34 GitHub Basics
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05:31:02 Open & Merge Pull Request
05:36:07 Jenkins - CI/CD
05:53:33 Hands-on
06:37:27 Docker - Containerization
06:49:25 What is DockerImage
06:52:21 What is Dockerfile
06:55:39 Docker Commands
07:01:34 Hands-on
07:13:48 Azure DevOps Basics
07:36:08 Case Study
07:37:38 Azure DevOps Testplan
07:46:58 Hands-on
08:03:07 Azure DevOps Artifacts
08:07:16 Demo
08:26:54 Azure Boards
08:30:25 Demo - Azure Boards Walkthrough
08:39:39 Azure DevOps Pipeline
08:43:32 Demo
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09:26:48 AWS DevOps Vs Azure DevOps
09:30:32 Azure DevOps Interview Questions& Answers

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⏩ NEW Top 10 Technologies To Learn In 2023 - https://youtu.be/udD_GQVDt5g

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🔥𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐆𝐨𝐨𝐠𝐥𝐞 𝐂𝐥𝐨𝐮𝐝 𝐏𝐥𝐚𝐭𝐟𝐨𝐫𝐦 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠: https://www.edureka.co/google-....cloud-architect-cert (𝐔𝐬𝐞 𝐂𝐨𝐝𝐞: 𝐘𝐎𝐔𝐓𝐔𝐁𝐄𝟐𝟎)
This "𝐆𝐨𝐨𝐠𝐥𝐞 𝐂𝐥𝐨𝐮𝐝 𝐀𝐧𝐭𝐡𝐨𝐬" video by Edureka will first explain what exactly is google cloud anthos, then talk about its components, features and benefits. Below are the topics covered in this Google Cloud Anthos Tutorial:
00:00:44 What is Google Cloud Platform?
00:02:00 What is Google Cloud Anthos?
00:05:25 Features of Google Cloud Anthos
00:07:20 Benefits of Google Cloud Anthos
00:10:07 Case Study on Google Cloud Anthos

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🔵 Post Graduate Program in DevOps with Purdue University: https://bit.ly/3Ov52lT

🔵 Advanced Certificate Program in Data Science with E&ICT Academy, IIT Guwahati: http://bit.ly/3V7ffrh

🔵 Advanced Certificate Program in Cloud Computing with E&ICT Academy, IIT Guwahati: https://bit.ly/43vmME8

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Помощь проекту: https://www.patreon.com/VertDider

Леонардо, то ли просто дрон с ногами, то ли не просто, умеет ходить по канату и кататься на скейтборде задом наперед, а его усовершенствованные потомки, возможно, когда-нибудь полетят в космос. По крайней мере, на это надеются его создатели. Дерек Маллер отправился посмотреть на Лео, посоревновался с ним и показал, в каких условиях его тестируют. Как думаете, у этого чуда техники большое будущее?

Перевод: Елена Смотрова
Редактура: Алексей Малов
Научная редактура: Павел Худик
Озвучка: Дмитрий Чепусов, Алексей Никитин, Алёна Соколова
Монтаж звука: Андрей Фокин
Монтаж видео: Джон Исмаилов

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🔥Enroll for Intellipaat's Azure Data Engineering Certification Course: https://intellipaat.com/azure-....data-engineer-certif

#AzureDataEngineerFullCourse #AzureDataFactoryTutorialForBeginners #AzureDataFactoryTutorial #AzureDataFactory #DataEngineeringCourse #AzureDataFactoryProject #Intellipaat

Looking to master Azure and kickstart your career as a Data Engineer? 🌟 This Azure Data Engineer Full Course 2025 is your one-stop solution! Designed specifically for beginners, this Azure Data Factory Tutorial for Beginners covers everything you need to know to work with Azure Data Factory effectively.

In this comprehensive Azure Data Factory Course, you’ll learn:
🎯 How to set up pipelines and dataflows in Azure Data Factory
🎯 Real-time scenarios and use cases for Azure Data Factory
🎯 How to use variables and expressions in Azure Data Factory
🎯 Hands-on projects to make you job-ready

Whether you’re a beginner or looking to enhance your skills, this Azure Data Engineer course ensures you gain practical knowledge and expertise to excel in your career. 💼

📖 Below are the concepts covered in this Azure Data Factory Tutorial For Beginners:
00:00:00 - Introduction to Azure Data Engineer Full Course
00:03:56 - What is Data Engineering?
00:10:30 - DP-203 Certification
00:40:53 - Storage and Azure Storage Benefits
01:06:41 - Replication
01:15:09 - Redundancy/Strategy Types: LRS
01:18:03 - Redundancy/Strategy Types: ZRS
01:21:40 - Redundancy/Strategy Types (Continued): Geo Redundant Storage (GRS)
01:33:24 - Redundancy/Strategy Types (Continued): Geo Zone Redundant Storage (GZRS)
01:37:40 - Redundancy/Strategy Types (Continued): Read Access GRS and Read Access GZRS
01:42:06 - Create Azure Storage Account
02:23:21 - Azure Governance Mechanism
02:29:28 - Why We Create Management Groups
02:35:56 - How to Create Policies
02:39:53 - How to Create Virtual Machines
02:41:58 - Resources Group
02:43:31 - Azure Policies and Azure RBAC
02:47:07 - Microsoft Entra Key
03:01:08 - What is RBAC?
03:12:42 - App Registration
03:34:28 - Data Lake Key Concepts
03:49:11 - What is ETL and ELT?
03:52:17 - Tools of Independent Compute
03:54:14 - What is IR?
03:57:59 - Version Control
04:01:05 - Cloud Deployment Models
04:08:21 - What is Data Factory Encryption?
04:24:47 - Steps of Azure Data Factory
04:47:23 - Working of Azure Data Factory (Continued): Access Azure Data Factory, Factory Resources
06:53:59 - SQL Database
08:04:36 - How to Create a Pipeline
08:35:37 - How to Run Queries
08:54:30 - What is Triggers?
08:57:43 - Adding Triggers to Data Pipelines
09:55:33 - What is Data Flow?
09:58:26 - What is Underline Compute?
10:06:41 - What is YARN?
11:02:04 - What is Aggregation?
11:14:35 - What is GIT and Its Branches?


🤔 What is Azure Data Factory, and why is it important?
Azure Data Factory (ADF) is a cloud-based ETL and data integration service by Microsoft. It's essential for building data pipelines, transforming data, and orchestrating workflows in the cloud.

🤔 Can beginners take this Azure Data Engineer course?
Absolutely! This course is specifically designed for beginners, starting with foundational concepts and advancing to real-world applications.

🤔 What can I expect from this Azure Data Factory tutorial for beginners?
You’ll get a deep dive into building pipelines, data flows, working with variables, and real-time scenarios, making it ideal for beginners looking to learn Azure Data Factory.

🤔 How will this Azure Data Factory course help in career growth?
By mastering Azure Data Factory and understanding its real-time applications, you'll be equipped to take on roles such as Azure Data Engineer, Data Analyst, or ETL Developer.

🎯 About the Course
This Azure Data Engineer Training helps learners refine their skills by implementing Azure data solutions like Azure SQL data warehouse, data factory, and more. Gain expertise in designing data solutions and security. Enroll now!

🎯 Key Features - (Course Features)
👉🏼 26 Hrs Instructor Led Training
👉🏼 26 Hrs Self-paced Videos
👉🏼 24 Hrs Project & Exercises
👉🏼 Certification
👉🏼 Job Assistance
👉🏼 Flexible Schedule
👉🏼 Lifetime Free Upgrade
👉🏼 Mentor Support

🎯 What’s Covered in This Program?
This Azure Data Engineer Course will prepare you for exams DP-203 for implementing and designing Azure data solutions, enabling you to design and perform data management, monitoring, security, and privacy using the complete Azure data services stack. Further, you will learn the following topics:
✅ Implement Azure Data Solution (DP 203)
✅ Execute a data storage solution
✅ Managing and developing data processing
✅ Monitoring and optimizing data solutions

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